CN115906213A - Editing method and system of visual chess evaluation statistical model - Google Patents
Editing method and system of visual chess evaluation statistical model Download PDFInfo
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Abstract
The invention provides an editing method and system of a visual chess evaluation statistical model, which solve the problems that a conventional deduction system chart is fixed, can only skip evaluation analysis, cannot be integrally displayed in a centralized manner and the like, and the scheme comprises the following steps: s1, collecting data from a chess simulation system, classifying the data, corresponding to tags in a data table, and storing the data in a data collection base; s2, evaluating the data according to a self-defined evaluation index, wherein the evaluation index comprises an interval index, a standard index and an interval index, inputting a minimum value, a maximum value and a relational operator, taking the input as a key field and the standard index, calling the acquired data table, selecting a field in the table as a standard, copying the field into the index, keeping the field unchanged, and defining the selected field as a key field; and S3, associating the acquired data with the evaluation index, adding an algorithm and a field to form an evaluation index system, and establishing a data model and visually displaying by taking the key field in the evaluation index as an interface.
Description
Technical Field
The invention relates to the technical field of war game deduction, in particular to an editing method and system of a visual war game evaluation statistical model.
Background
The evaluation statistics plays an important role in the demonstration of wargame deduction and simulation, and when the deduction process or the duplication process is carried out, the effects and the current situation of behaviors such as war losses, striking, reconnaissance and the like of two current deductions can be more intuitively understood through chart display by using a defined evaluation system, so that data bases are provided for duplication research and subsequent research.
At present, most deduction systems carry evaluation statistical analysis, but the evaluation system can only modify index parameters and cannot establish an evaluation model, so that evaluation analysis cannot be expanded, and analysis and solidification of deduction data are realized.
Meanwhile, data presented by most of the existing deduction systems are fixed charts, and only certain evaluation statistical analysis content can be checked through interface skipping, but often users need to display certain items in a centralized manner as one system for display, and can customize a plurality of systems.
Disclosure of Invention
The invention provides xx and xxx.
In order to solve the technical problems, the invention adopts the technical scheme that: an editing method of a visual military chess evaluation statistical model comprises the following steps:
s1, collecting data from a chess simulation system, classifying the data, corresponding to tags in a data table, and storing the data in a data collection base;
s2, evaluating the data in the data acquisition library according to self-defined evaluation indexes, wherein the evaluation indexes comprise interval indexes and standard indexes, and are specifically set as follows,
interval index, inputting minimum value, maximum value and relation operator, using the input as key field,
standard index, calling the collected data table, selecting the field in the table as standard and copying the standard field into the index, keeping the field unchanged, defining the selected field as key field,
and S3, associating the acquired data with the evaluation index, adding an algorithm and a field to form an evaluation index system, taking a key field in the evaluation index as an interface, establishing a data model corresponding to the evaluation index system, and displaying the data model visually through a screen.
Further, the data classified in step S1 includes built-in data, custom data, and derived data, and the data table includes a configuration table, a parameter table, and a dynamic data table.
Further, in step S2, the index system is set according to the percentage, the weight defaults to 100, and after the weight is modified, the index is changed correspondingly but the overall ratio is not changed.
Further, the visualization display in the step S3 is realized through a chart control and a text control, the chart control is used for multi-dimensional graphical representation of the data model, and the text control is used for editing the content of the data model.
An editing system of a visual chess evaluation statistical model comprises:
the acquisition module is used for acquiring data in the chess simulation system, and storing the data after classification corresponding to the labels in the data table;
the evaluation module is used for evaluating the acquired data through the user-defined index;
the design module is used for associating the data with the evaluation index, simultaneously adding an algorithm and a field, and correspondingly constructing a data model;
and the display module is used for editing the data model content and visualizing the data model in a chart mode.
An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the editing method of the visual chess evaluation statistical model according to any one of claims 1 to 4 when executing the program.
A non-transitory computer readable storage medium, having stored thereon a computer program, which when executed by a processor, is adapted to implement the steps of the editing method of a visual chess evaluation statistical model according to any one of claims 1 to 4.
Compared with the prior art, the invention has the beneficial effects that: the invention relates the collected data and the set evaluation index through the connection by the control correlation mode, visually designs the evaluation statistical model, customizes the display layout and content of a large data screen by using charts such as a line graph, a curve graph, a bar graph and the like, displays the evaluation index analysis and the statistical data analysis of the chess deduction, and has great significance for the chess deduction simulation.
Drawings
The disclosure of the present invention is illustrated with reference to the accompanying drawings. It is to be understood that the drawings are designed solely for the purposes of illustration and not as a definition of the limits of the invention. In the drawings, like reference numerals are used to refer to like parts. Wherein:
fig. 1 schematically shows a schematic diagram of a proposed system composition according to an embodiment of the present invention.
Detailed Description
It is easily understood that according to the technical solution of the present invention, a person skilled in the art can propose various alternative structures and implementation ways without changing the spirit of the present invention. Therefore, the following detailed description and the accompanying drawings are merely illustrative of the technical aspects of the present invention, and should not be construed as all of the present invention or as limitations or limitations on the technical aspects of the present invention.
An embodiment according to the present invention is shown in connection with fig. 1.
A method for editing a visual military chess evaluation statistical model specifically comprises the following steps:
s1, collecting data from a chess simulation system, classifying the data, corresponding to tags in a data table, and storing the data in a data collection base;
s2, evaluating the data in the data acquisition library according to self-defined evaluation indexes, wherein the evaluation indexes comprise interval indexes and standard indexes, and are specifically set as follows,
interval index, inputting minimum value, maximum value and relation operator, using the input as key field,
standard index, calling the collected data table, selecting the field in the table as standard and copying the standard to the index, keeping the field unchanged, defining the selected field as key field,
and S3, associating the acquired data with the evaluation index, adding an algorithm and a field to form an evaluation index system, taking a key field in the evaluation index as an interface, establishing a data model corresponding to the evaluation index system, and displaying the data model in a visualized manner through a screen.
As shown in fig. 1, the following specific system construction process is further described for this method:
in this embodiment, the system mainly comprises an acquisition module, an evaluation module, a design module, and a display module.
For the acquisition module, the acquired data can be divided into three categories, in turn,
data are built in: the system embeds preset parameter tables, configuration tables and related data into the system in a development stage;
self-defining data: during the use process of the system, the data sheet and the data are customized by each tool or subsystem;
deduction data: the data generated in the deduction process is defined by other systems, namely dynamic data.
The data classified corresponds to the labels in the collected data table, and the editable labels specifically comprise,
and (4) newly building a label: label names need to be typed, duplicate names need to be made, illegal character judgment is carried out, 1-4 characters are limited, and a new label with duplicate names cannot be created;
and (4) deleting the label: after deleting, removing the labels set under all the tables;
and label renaming: the tags can be renamed, and the tags hung under the table are renamed at the same time after renaming;
adding a label: labels can be added to individual or batch data tables;
for the evaluation module, the evaluation statistics tool synchronizes all tables and data generated by other systems into the evaluation repository through the interface, while editable for evaluation management specifically includes,
newly adding: defining evaluation item names, judging duplicate names and illegal characters, limiting 1-10 characters, if no selection grouping is performed, bringing the evaluation items into a default group, and setting the newly-established evaluation default at the end of the group;
copying: copying a current evaluation named as the original evaluation name +1 (if the evaluation has a double name, the evaluation is performed by +2, and so on);
selecting the type: selecting an index type when establishing evaluation, wherein the index type cannot be changed after the evaluation;
type (2): the types are divided into interval indexes and standard indexes;
renaming can be carried out on the evaluation, and renaming and illegal character judgment are needed to be carried out, and judgment is added at the same time;
default grouping: self-contained default grouping and non-deletable;
newly building: inputting a group name, judging the group name by duplication and illegal characters, limiting 1-10 characters, and arranging a newly-built group at the end by default;
and (3) deleting: if no model table exists in the group, allowing the group to be deleted, otherwise, not allowing the group to be deleted;
renaming: renaming the group, wherein the group name needs to be subjected to renaming and illegal character judgment, and 1-10 characters are limited;
grouping: the evaluations may be grouped individually or in batches;
sorting: intra-group ordering is supported, as is change grouping. Packet sequencing, which supports the sequencing of packets; ordering in groups, supporting the ordering of rule items;
and (3) inquiring: fuzzy query of keywords is supported, and a matching range comprises a rule item name;
setting specific indexes of the evaluation indexes:
interval index interval: inputting minimum and maximum values and selecting a relation operator which is an integer or a decimal and defaults to be a key field;
indexes are as follows: filling integers according to the percentage as a quantization index;
and (3) weighting: defaults to 100, and can be adjusted in model design;
standard indexes are as follows: calling a collected data table (which is a table with data and can only be temporarily collected built-in data and custom data), selecting a field as a standard, copying the field into an index, not following dynamic change, and defining a certain field as a key field;
indexes are as follows: filling integers according to the percentage as a quantization index;
and (3) weighting: default 100, adjustable in model design;
the number of indexes is as follows: index line data may be added or deleted.
The design module is responsible for forming an evaluation index system after associating the data, the data sheet and the evaluation index, and sequentially and correspondingly constructing a data model.
Editable management of models:
newly building: inputting a model name, judging a duplicate name and an illegal character, limiting 1-10 characters, if grouping is not selected, bringing the characters into a default group, and defaulting a newly-built model table at the end of the group;
copying: copying a current model, and naming the current model as an original model name +1 (if the current model has a duplicate name +2, and so on);
and (3) deleting: whether the model is called in the data large-screen setting needs to be detected, if the model is called, the model cannot be deleted, and the relevant calling relation needs to be manually deleted firstly; if the call is not available, deleting the call after secondary confirmation;
renaming: the model table needs to judge duplicate names and illegal characters, and 1-10 characters are limited;
default grouping: self-contained default grouping and non-deletable;
newly building: inputting a group name, judging the group name by duplication and illegal characters, limiting 1-10 characters, and arranging a newly-built group at the end by default;
and (3) deleting: if no model table exists in the group, allowing the group to be deleted, otherwise, not allowing the group to be deleted;
renaming: renaming the groups, wherein the group names need to be subjected to renaming and illegal character judgment, and 1-10 characters are limited;
grouping: models can be grouped individually or in batches;
sorting: intra-group ordering is supported, as is change grouping. Packet sequencing, which supports the sequencing of packets; ordering in the group, and supporting the ordering of the rule items;
inquiring: fuzzy query of keywords is supported, and the matching range comprises the names of the rule items.
Similarly, in the model design process, fields and algorithms are added in a model table Europe, the construction of a data model table is completed by combining evaluation indexes and the like, and during specific design, the added tables or the evaluation indexes can be put into a model design panel and are associated or added with the fields through connecting lines, and the operation mode comprises the following steps:
adding data: a data table is taken from the collected data and added into the design of the model;
and table association: two tables correspond to a key field;
adding fields: selecting an add field from the table to the model design;
newly adding fields: adding a field, inputting the field name, and limiting 1-10 characters;
the data type is as follows: one must select a data type, int, integer; float, floating point type; string, character type;
and (3) field definition: taking a new value formed by a field in the existing model table through an algorithm formula or judgment as the field value;
calling an evaluation index: selecting a certain evaluation index to be dragged into a model design panel, connecting a field into a key field interface of the evaluation index through a connecting wire, setting the evaluation weight as default to 100, modifying again, wherein the requirement > =1, the output of the evaluation index is automatically used as a model field, and the value output by the field can be selected to be an integer or decimal and is reserved for several bits;
deleting the field: if the associated fields or the custom fields are called in the model, the associated fields or the custom fields cannot be deleted, the related calling relation needs to be deleted firstly, and if the associated fields or the custom fields are not called, the associated fields or the custom fields are deleted after secondary confirmation.
And the display module is used for displaying and editing the data model in a visual mode through a screen after the data model is constructed.
Editing management for screens:
newly adding: newly increased data large screens are supported, the data large screen names need to be defined when the data large screens are newly increased, and the duplicate names, special characters and character overlength judgment need to be carried out;
and (4) modifying the name: the name of the data large screen is allowed to be modified, and the previous hyperchain is not influenced;
and (3) deleting: the deletion of the unnecessary data large screen is supported, and if the current data large screen is referred by the hyperlink, the hyperlink is invalid when being clicked;
set to default: and setting the large screen as a default large screen when entering an evaluation interface after deduction is finished.
When the model is displayed, the chart control and the character control in the control library can be called, and the chart control editing step comprises the following steps:
and (4) classification: supporting selection of radar maps, line graphs, bar graphs and pie graphs;
x-axis-category (dimension): the method supports that certain dimension information is called from a data model as category information (namely column names in a table);
y-axis-polymerization (dimension): the method comprises the steps that certain dimension information is called from a data model and serves as aggregation information (namely titles of a plurality of Y axes) displayed by the Y axes;
y-axis-value (measure): the method supports that certain measurement information is called from a data model and used as value information (namely a specific value of a Y axis) displayed by the Y axis;
polymerization mode: after the X-axis-category and the Y-axis-aggregation are selected, aggregation processing needs to be carried out on measurement data under the same dimension information; processing the Y-axis-aggregation, and then processing the X-axis-classification;
polymerization mode: summing, wherein the measurement data under the same dimension is subjected to summing processing; averaging the measurement data in the same dimension; counting, namely calculating the number of data pieces by using the measurement data in the same dimension; counting the duplication, namely calculating the number of non-repeated data pieces by using the measurement data under the same dimensionality; the maximum value is the measured data under the same dimension and is returned to the maximum value; the minimum value is returned to the measurement data under the same dimension; the initial value, the measurement data under the same dimension, returns the value of the 0 th round; returning the final value, namely the measurement data under the same dimension, to the value of the last 1 round;
and (3) Y-axis display screening: supporting a selection user to automatically open a check box of a Y-axis display (the pie chart has no setting);
a display data table: and supporting selection of whether to display a specific data table or not, and otherwise, only displaying the data graph.
The text control editing step comprises the following steps:
and (3) editing content: supporting the editing content default centering alignment of the text content;
setting characters: the method supports the setting of the RGBA and the font size of the characters;
setting a background: the method comprises the following steps of supporting the setting of RGBA of a background, and setting the RGBA as white and fully transparent by default;
frame setting: the RGBA of the frame is supported to be set, and the default is white and fully transparent;
and (3) hyperlink: and a hyperlink function is supported, and after a user clicks a font control, other set data large screens are directly opened.
The problem of multi-table association is solved through key field association, a main field is needed in evaluation statistics, the field is generally used as the dimension of a chart and is X-axis data, other fields are used as Y-axis data, therefore, all tables are associated through the key field, association cannot be carried out if the key field is not used, a formula is built through a defined mathematical function through a custom field, parameters in the formula can be fixed values, and the defined field can also be called from a current data model.
Finally, the user can customize the setting of indexes such as evaluation types, weights, index values and the like in the evaluation statistical model, and can also customize the display layout and content of a large screen of data by using charts such as line graphs, curve graphs, bar graphs and the like, so that the subsequent operation of the chess deduction system is facilitated.
The technical scope of the present invention is not limited to the above description, and those skilled in the art can make various changes and modifications to the above-described embodiments without departing from the technical spirit of the present invention, and such changes and modifications should fall within the protective scope of the present invention.
Claims (7)
1. A visual chess evaluation statistical model editing method is characterized by comprising the following steps:
s1, collecting data from a chess simulation system, classifying the data, corresponding to tags in a data table, and storing the data in a data collection base;
s2, evaluating the data in the data acquisition library according to self-defined evaluation indexes, wherein the evaluation indexes comprise interval indexes and standard indexes, and are specifically set as follows,
interval index, inputting minimum value, maximum value and relation operator, using the input as key field,
standard index, calling the collected data table, selecting the field in the table as standard and copying the standard field into the index, keeping the field unchanged, defining the selected field as key field,
and S3, associating the acquired data with the evaluation index, adding an algorithm and a field to form an evaluation index system, taking a key field in the evaluation index as an interface, establishing a data model corresponding to the evaluation index system, and displaying the data model in a visualized manner through a screen.
2. The editing method of the visual chess evaluation statistical model according to claim 1, characterized in that: the data classified in the step S1 comprises built-in data, custom data and deduction data, and the data table comprises a configuration table, a parameter table and a dynamic data table.
3. The editing method of the visual chess evaluation statistical model according to claim 1, characterized in that: in the step S2, the index system is set according to the percentage, the weight defaults to 100, and after the weight is modified, the index value is correspondingly changed but the overall proportion is not changed.
4. The editing method of the visual chess evaluation statistical model according to claim 1, characterized in that: the visual display in the step S3 is realized by a chart control and a text control, the chart control is used for multi-dimensional graphical representation of the data model, and the text control is used for editing the content of the data model.
5. The utility model provides an editing system of visual war chess aassessment statistical model which characterized in that includes:
the acquisition module is used for acquiring data in the military chess simulation system, and storing the data after classification corresponding to the labels in the data table;
the evaluation module is used for evaluating the acquired data through the user-defined index;
the design module is used for associating the data with the evaluation index, simultaneously adding an algorithm and a field, and correspondingly constructing a data model;
and the display module is used for editing the content of the data model and visualizing the data model in a chart mode.
6. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the editing method of the visual chess evaluation statistical model according to any one of claims 1 to 4 when executing the program.
7. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program is used for implementing the steps of the editing method of the visual chess evaluation statistical model in any one of the above claims 1 to 4 when being executed by a processor.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117114953A (en) * | 2023-10-25 | 2023-11-24 | 中国电子科技集团公司第十五研究所 | Method for dynamically evaluating and constructing chess deduction system, server and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117114953A (en) * | 2023-10-25 | 2023-11-24 | 中国电子科技集团公司第十五研究所 | Method for dynamically evaluating and constructing chess deduction system, server and storage medium |
| CN117114953B (en) * | 2023-10-25 | 2024-01-23 | 中国电子科技集团公司第十五研究所 | Method for dynamically evaluating and constructing chess deduction system, server and storage medium |
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